{"id":9069,"date":"2024-01-02T14:03:06","date_gmt":"2024-01-02T06:03:06","guid":{"rendered":"\/?p=9069"},"modified":"2024-01-02T14:03:06","modified_gmt":"2024-01-02T06:03:06","slug":"opencv-%e5%9b%be%e5%83%8f%e5%a4%84%e7%90%86","status":"publish","type":"post","link":"\/?p=9069","title":{"rendered":"OpenCV-\u56fe\u50cf\u5904\u7406"},"content":{"rendered":"<h3>\u7070\u5ea6\u56fe<\/h3>\n<pre><code class=\"language-python\">import cv2 #opencv\u8bfb\u53d6\u7684\u683c\u5f0f\u662fBGR\nimport numpy as np\nimport matplotlib.pyplot as plt#Matplotlib\u662fRGB\n%matplotlib inline \n\nimg=cv2.imread(&#039;cat.jpg&#039;)\nimg_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\nimg_gray.shape<\/code><\/pre>\n<pre><code>(414, 500)<\/code><\/pre>\n<pre><code class=\"language-python\">cv2.imshow(&quot;img_gray&quot;, img_gray)\ncv2.waitKey(0)    \ncv2.destroyAllWindows() <\/code><\/pre>\n<h3>HSV<\/h3>\n<ul>\n<li>H - \u8272\u8c03\uff08\u4e3b\u6ce2\u957f\uff09\u3002 <\/li>\n<li>S - \u9971\u548c\u5ea6\uff08\u7eaf\u5ea6\/\u989c\u8272\u7684\u9634\u5f71\uff09\u3002 <\/li>\n<li>V\u503c\uff08\u5f3a\u5ea6\uff09<\/li>\n<\/ul>\n<pre><code class=\"language-python\">hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)\n\ncv2.imshow(&quot;hsv&quot;, hsv)\ncv2.waitKey(0)    \ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u56fe\u50cf\u9608\u503c<\/h3>\n<h4>ret, dst = cv2.threshold(src, thresh, maxval, type)<\/h4>\n<ul>\n<li>\n<p>src\uff1a \u8f93\u5165\u56fe\uff0c\u53ea\u80fd\u8f93\u5165\u5355\u901a\u9053\u56fe\u50cf\uff0c\u901a\u5e38\u6765\u8bf4\u4e3a\u7070\u5ea6\u56fe<\/p>\n<\/li>\n<li>\n<p>dst\uff1a \u8f93\u51fa\u56fe<\/p>\n<\/li>\n<li>\n<p>thresh\uff1a \u9608\u503c<\/p>\n<\/li>\n<li>\n<p>maxval\uff1a \u5f53\u50cf\u7d20\u503c\u8d85\u8fc7\u4e86\u9608\u503c\uff08\u6216\u8005\u5c0f\u4e8e\u9608\u503c\uff0c\u6839\u636etype\u6765\u51b3\u5b9a\uff09\uff0c\u6240\u8d4b\u4e88\u7684\u503c<\/p>\n<\/li>\n<li>\n<p>type\uff1a\u4e8c\u503c\u5316\u64cd\u4f5c\u7684\u7c7b\u578b\uff0c\u5305\u542b\u4ee5\u4e0b5\u79cd\u7c7b\u578b\uff1a cv2.THRESH_BINARY\uff1b cv2.THRESH_BINARY_INV\uff1b cv2.THRESH_TRUNC\uff1b cv2.THRESH_TOZERO\uff1bcv2.THRESH_TOZERO_INV<\/p>\n<\/li>\n<li>\n<p>cv2.THRESH_BINARY \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u8d85\u8fc7\u9608\u503c\u90e8\u5206\u53d6maxval\uff08\u6700\u5927\u503c\uff09\uff0c\u5426\u5219\u53d60<\/p>\n<\/li>\n<li>\n<p>cv2.THRESH_BINARY_INV \u00a0 \u00a0THRESH_BINARY\u7684\u53cd\u8f6c<\/p>\n<\/li>\n<li>\n<p>cv2.THRESH_TRUNC \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u5927\u4e8e\u9608\u503c\u90e8\u5206\u8bbe\u4e3a\u9608\u503c\uff0c\u5426\u5219\u4e0d\u53d8<\/p>\n<\/li>\n<li>\n<p>cv2.THRESH_TOZERO \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u5927\u4e8e\u9608\u503c\u90e8\u5206\u4e0d\u6539\u53d8\uff0c\u5426\u5219\u8bbe\u4e3a0<\/p>\n<\/li>\n<li>\n<p>cv2.THRESH_TOZERO_INV \u00a0THRESH_TOZERO\u7684\u53cd\u8f6c<\/p>\n<\/li>\n<\/ul>\n<pre><code class=\"language-python\">ret, thresh1 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)\nret, thresh2 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV)\nret, thresh3 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TRUNC)\nret, thresh4 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO)\nret, thresh5 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO_INV)\n\ntitles = [&#039;Original Image&#039;, &#039;BINARY&#039;, &#039;BINARY_INV&#039;, &#039;TRUNC&#039;, &#039;TOZERO&#039;, &#039;TOZERO_INV&#039;]\nimages = [img, thresh1, thresh2, thresh3, thresh4, thresh5]\n\nfor i in range(6):\n    plt.subplot(2, 3, i + 1), plt.imshow(images[i], &#039;gray&#039;)\n    plt.title(titles[i])\n    plt.xticks([]), plt.yticks([])\nplt.show()<\/code><\/pre>\n<p>\u200b<br \/>\n<img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/%E5%9B%BE%E5%83%8F%E5%A4%84%E7%90%86_6_0.png\" alt=\"png\" \/><br \/>\n\u200b    <\/p>\n<h3>\u56fe\u50cf\u5e73\u6ed1<\/h3>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/image.png\" alt=\"image.png\" \/><\/p>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;lenaNoise.png&#039;)\n\ncv2.imshow(&#039;img&#039;, img)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u5747\u503c\u6ee4\u6ce2\n# \u7b80\u5355\u7684\u5e73\u5747\u5377\u79ef\u64cd\u4f5c\nblur = cv2.blur(img, (3, 3))\n\ncv2.imshow(&#039;blur&#039;, blur)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u65b9\u6846\u6ee4\u6ce2\n# \u57fa\u672c\u548c\u5747\u503c\u4e00\u6837\uff0c\u53ef\u4ee5\u9009\u62e9\u5f52\u4e00\u5316\nbox = cv2.boxFilter(img,-1,(3,3), normalize=True)  \n\ncv2.imshow(&#039;box&#039;, box)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u65b9\u6846\u6ee4\u6ce2\n# \u57fa\u672c\u548c\u5747\u503c\u4e00\u6837\uff0c\u53ef\u4ee5\u9009\u62e9\u5f52\u4e00\u5316,\u5bb9\u6613\u8d8a\u754c\nbox = cv2.boxFilter(img,-1,(3,3), normalize=False)  \n\ncv2.imshow(&#039;box&#039;, box)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u9ad8\u65af\u6ee4\u6ce2\n# \u9ad8\u65af\u6a21\u7cca\u7684\u5377\u79ef\u6838\u91cc\u7684\u6570\u503c\u662f\u6ee1\u8db3\u9ad8\u65af\u5206\u5e03\uff0c\u76f8\u5f53\u4e8e\u66f4\u91cd\u89c6\u4e2d\u95f4\u7684\naussian = cv2.GaussianBlur(img, (5, 5), 1)  \n\ncv2.imshow(&#039;aussian&#039;, aussian)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u4e2d\u503c\u6ee4\u6ce2\n# \u76f8\u5f53\u4e8e\u7528\u4e2d\u503c\u4ee3\u66ff\nmedian = cv2.medianBlur(img, 5)  # \u4e2d\u503c\u6ee4\u6ce2\n\ncv2.imshow(&#039;median&#039;, median)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u5c55\u793a\u6240\u6709\u7684\nres = np.hstack((blur,aussian,median))\n#print (res)\ncv2.imshow(&#039;median vs average&#039;, res)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u5f62\u6001\u5b66-\u8150\u8680\u64cd\u4f5c<\/h3>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;dige.png&#039;)\n\ncv2.imshow(&#039;img&#039;, img)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">kernel = np.ones((3,3),np.uint8) \nerosion = cv2.erode(img,kernel,iterations = 1)\n\ncv2.imshow(&#039;erosion&#039;, erosion)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">pie = cv2.imread(&#039;pie.png&#039;)\n\ncv2.imshow(&#039;pie&#039;, pie)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">kernel = np.ones((30,30),np.uint8) \nerosion_1 = cv2.erode(pie,kernel,iterations = 1)\nerosion_2 = cv2.erode(pie,kernel,iterations = 2)\nerosion_3 = cv2.erode(pie,kernel,iterations = 3)\nres = np.hstack((erosion_1,erosion_2,erosion_3))\ncv2.imshow(&#039;res&#039;, res)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u5f62\u6001\u5b66-\u81a8\u80c0\u64cd\u4f5c<\/h3>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;dige.png&#039;)\ncv2.imshow(&#039;img&#039;, img)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">kernel = np.ones((3,3),np.uint8) \ndige_erosion = cv2.erode(img,kernel,iterations = 1)\n\ncv2.imshow(&#039;erosion&#039;, erosion)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">kernel = np.ones((3,3),np.uint8) \ndige_dilate = cv2.dilate(dige_erosion,kernel,iterations = 1)\n\ncv2.imshow(&#039;dilate&#039;, dige_dilate)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">pie = cv2.imread(&#039;pie.png&#039;)\n\nkernel = np.ones((30,30),np.uint8) \ndilate_1 = cv2.dilate(pie,kernel,iterations = 1)\ndilate_2 = cv2.dilate(pie,kernel,iterations = 2)\ndilate_3 = cv2.dilate(pie,kernel,iterations = 3)\nres = np.hstack((dilate_1,dilate_2,dilate_3))\ncv2.imshow(&#039;res&#039;, res)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u5f00\u8fd0\u7b97\u4e0e\u95ed\u8fd0\u7b97<\/h3>\n<pre><code class=\"language-python\"># \u5f00\uff1a\u5148\u8150\u8680\uff0c\u518d\u81a8\u80c0\nimg = cv2.imread(&#039;dige.png&#039;)\n\nkernel = np.ones((5,5),np.uint8) \nopening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)\n\ncv2.imshow(&#039;opening&#039;, opening)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\"># \u95ed\uff1a\u5148\u81a8\u80c0\uff0c\u518d\u8150\u8680\nimg = cv2.imread(&#039;dige.png&#039;)\n\nkernel = np.ones((5,5),np.uint8) \nclosing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)\n\ncv2.imshow(&#039;closing&#039;, closing)\ncv2.waitKey(0)\ncv2.destroyAllWindows()\n<\/code><\/pre>\n<h3>\u68af\u5ea6\u8fd0\u7b97<\/h3>\n<pre><code class=\"language-python\"># \u68af\u5ea6=\u81a8\u80c0-\u8150\u8680\npie = cv2.imread(&#039;pie.png&#039;)\nkernel = np.ones((7,7),np.uint8) \ndilate = cv2.dilate(pie,kernel,iterations = 5)\nerosion = cv2.erode(pie,kernel,iterations = 5)\n\nres = np.hstack((dilate,erosion))\n\ncv2.imshow(&#039;res&#039;, res)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">gradient = cv2.morphologyEx(pie, cv2.MORPH_GRADIENT, kernel)\n\ncv2.imshow(&#039;gradient&#039;, gradient)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u793c\u5e3d\u4e0e\u9ed1\u5e3d<\/h3>\n<ul>\n<li>\u793c\u5e3d = \u539f\u59cb\u8f93\u5165-\u5f00\u8fd0\u7b97\u7ed3\u679c<\/li>\n<li>\u9ed1\u5e3d = \u95ed\u8fd0\u7b97-\u539f\u59cb\u8f93\u5165<\/li>\n<\/ul>\n<pre><code class=\"language-python\">#\u793c\u5e3d\nimg = cv2.imread(&#039;dige.png&#039;)\ntophat = cv2.morphologyEx(img, cv2.MORPH_TOPHAT, kernel)\ncv2.imshow(&#039;tophat&#039;, tophat)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">#\u9ed1\u5e3d\nimg = cv2.imread(&#039;dige.png&#039;)\nblackhat  = cv2.morphologyEx(img,cv2.MORPH_BLACKHAT, kernel)\ncv2.imshow(&#039;blackhat &#039;, blackhat )\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h3>\u56fe\u50cf\u68af\u5ea6-Sobel\u7b97\u5b50<\/h3>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/sobel_1.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;pie.png&#039;,cv2.IMREAD_GRAYSCALE)\ncv2.imshow(&quot;img&quot;,img)\ncv2.waitKey()\ncv2.destroyAllWindows()<\/code><\/pre>\n<p>dst = cv2.Sobel(src, ddepth, dx, dy, ksize)<\/p>\n<ul>\n<li>ddepth:\u56fe\u50cf\u7684\u6df1\u5ea6<\/li>\n<li>dx\u548cdy\u5206\u522b\u8868\u793a\u6c34\u5e73\u548c\u7ad6\u76f4\u65b9\u5411<\/li>\n<li>ksize\u662fSobel\u7b97\u5b50\u7684\u5927\u5c0f<\/li>\n<\/ul>\n<pre><code class=\"language-python\">def cv_show(img,name):\n    cv2.imshow(name,img)\n    cv2.waitKey()\n    cv2.destroyAllWindows()<\/code><\/pre>\n<pre><code class=\"language-python\">sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)\n\ncv_show(sobelx,&#039;sobelx&#039;)<\/code><\/pre>\n<p>\u767d\u5230\u9ed1\u662f\u6b63\u6570\uff0c\u9ed1\u5230\u767d\u5c31\u662f\u8d1f\u6570\u4e86\uff0c\u6240\u6709\u7684\u8d1f\u6570\u4f1a\u88ab\u622a\u65ad\u62100\uff0c\u6240\u4ee5\u8981\u53d6\u7edd\u5bf9\u503c<\/p>\n<pre><code class=\"language-python\">sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)\nsobelx = cv2.convertScaleAbs(sobelx)\ncv_show(sobelx,&#039;sobelx&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)\nsobely = cv2.convertScaleAbs(sobely)  \ncv_show(sobely,&#039;sobely&#039;)<\/code><\/pre>\n<p>\u5206\u522b\u8ba1\u7b97x\u548cy\uff0c\u518d\u6c42\u548c<\/p>\n<pre><code class=\"language-python\">sobelxy = cv2.addWeighted(sobelx,0.5,sobely,0.5,0)\ncv_show(sobelxy,&#039;sobelxy&#039;)<\/code><\/pre>\n<p>\u4e0d\u5efa\u8bae\u76f4\u63a5\u8ba1\u7b97<\/p>\n<pre><code class=\"language-python\">sobelxy=cv2.Sobel(img,cv2.CV_64F,1,1,ksize=3)\nsobelxy = cv2.convertScaleAbs(sobelxy) \ncv_show(sobelxy,&#039;sobelxy&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;lena.jpg&#039;,cv2.IMREAD_GRAYSCALE)\ncv_show(img,&#039;img&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;lena.jpg&#039;,cv2.IMREAD_GRAYSCALE)\nsobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)\nsobelx = cv2.convertScaleAbs(sobelx)\nsobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)\nsobely = cv2.convertScaleAbs(sobely)\nsobelxy = cv2.addWeighted(sobelx,0.5,sobely,0.5,0)\ncv_show(sobelxy,&#039;sobelxy&#039;)<\/code><\/pre>\n<p>img = cv2.imread('lena.jpg',cv2.IMREAD_GRAYSCALE)<\/p>\n<p>sobelxy=cv2.Sobel(img,cv2.CV_64F,1,1,ksize=3)<br \/>\nsobelxy = cv2.convertScaleAbs(sobelxy)<br \/>\ncv_show(sobelxy,'sobelxy')<\/p>\n<h3>\u56fe\u50cf\u68af\u5ea6-Scharr\u7b97\u5b50<\/h3>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/scharr.png\" alt=\"title\" \/><\/p>\n<h3>\u56fe\u50cf\u68af\u5ea6-laplacian\u7b97\u5b50<\/h3>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/l.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">#\u4e0d\u540c\u7b97\u5b50\u7684\u5dee\u5f02\nimg = cv2.imread(&#039;lena.jpg&#039;,cv2.IMREAD_GRAYSCALE)\nsobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)\nsobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)\nsobelx = cv2.convertScaleAbs(sobelx)   \nsobely = cv2.convertScaleAbs(sobely)  \nsobelxy =  cv2.addWeighted(sobelx,0.5,sobely,0.5,0)  \n\nscharrx = cv2.Scharr(img,cv2.CV_64F,1,0)\nscharry = cv2.Scharr(img,cv2.CV_64F,0,1)\nscharrx = cv2.convertScaleAbs(scharrx)   \nscharry = cv2.convertScaleAbs(scharry)  \nscharrxy =  cv2.addWeighted(scharrx,0.5,scharry,0.5,0) \n\nlaplacian = cv2.Laplacian(img,cv2.CV_64F)\nlaplacian = cv2.convertScaleAbs(laplacian)   \n\nres = np.hstack((sobelxy,scharrxy,laplacian))\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;lena.jpg&#039;,cv2.IMREAD_GRAYSCALE)\ncv_show(img,&#039;img&#039;)<\/code><\/pre>\n<h3>Canny\u8fb9\u7f18\u68c0\u6d4b<\/h3>\n<ul>\n<li>\n<p>1)        \u4f7f\u7528\u9ad8\u65af\u6ee4\u6ce2\u5668\uff0c\u4ee5\u5e73\u6ed1\u56fe\u50cf\uff0c\u6ee4\u9664\u566a\u58f0\u3002<\/p>\n<\/li>\n<li>\n<p>2)        \u8ba1\u7b97\u56fe\u50cf\u4e2d\u6bcf\u4e2a\u50cf\u7d20\u70b9\u7684\u68af\u5ea6\u5f3a\u5ea6\u548c\u65b9\u5411\u3002<\/p>\n<\/li>\n<li>\n<p>3)        \u5e94\u7528\u975e\u6781\u5927\u503c\uff08Non-Maximum Suppression\uff09\u6291\u5236\uff0c\u4ee5\u6d88\u9664\u8fb9\u7f18\u68c0\u6d4b\u5e26\u6765\u7684\u6742\u6563\u54cd\u5e94\u3002<\/p>\n<\/li>\n<li>\n<p>4)        \u5e94\u7528\u53cc\u9608\u503c\uff08Double-Threshold\uff09\u68c0\u6d4b\u6765\u786e\u5b9a\u771f\u5b9e\u7684\u548c\u6f5c\u5728\u7684\u8fb9\u7f18\u3002<\/p>\n<\/li>\n<li>\n<p>5)        \u901a\u8fc7\u6291\u5236\u5b64\u7acb\u7684\u5f31\u8fb9\u7f18\u6700\u7ec8\u5b8c\u6210\u8fb9\u7f18\u68c0\u6d4b\u3002<\/p>\n<\/li>\n<\/ul>\n<h4>1:\u9ad8\u65af\u6ee4\u6ce2\u5668<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/canny_1.png\" alt=\"title\" \/><\/p>\n<h4>2:\u68af\u5ea6\u548c\u65b9\u5411<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/canny_2.png\" alt=\"title\" \/><\/p>\n<h4>3\uff1a\u975e\u6781\u5927\u503c\u6291\u5236<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/canny_3.png\" alt=\"title\" \/><\/p>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/canny_6.png\" alt=\"title\" \/><\/p>\n<h4>4\uff1a\u53cc\u9608\u503c\u68c0\u6d4b<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/canny_5.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">img=cv2.imread(&quot;lena.jpg&quot;,cv2.IMREAD_GRAYSCALE)\n\nv1=cv2.Canny(img,80,150)\nv2=cv2.Canny(img,50,100)\n\nres = np.hstack((v1,v2))\ncv_show(res,&#039;res&#039;)\n<\/code><\/pre>\n<pre><code class=\"language-python\">img=cv2.imread(&quot;car.png&quot;,cv2.IMREAD_GRAYSCALE)\n\nv1=cv2.Canny(img,120,250)\nv2=cv2.Canny(img,50,100)\n\nres = np.hstack((v1,v2))\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<h3>\u56fe\u50cf\u91d1\u5b57\u5854<\/h3>\n<ul>\n<li>\u9ad8\u65af\u91d1\u5b57\u5854<\/li>\n<li>\u62c9\u666e\u62c9\u65af\u91d1\u5b57\u5854<\/li>\n<\/ul>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/Pyramid_1.png\" alt=\"title\" \/><\/p>\n<h4>\u9ad8\u65af\u91d1\u5b57\u5854\uff1a\u5411\u4e0b\u91c7\u6837\u65b9\u6cd5\uff08\u7f29\u5c0f\uff09<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/Pyramid_2.png\" alt=\"title\" \/><\/p>\n<h4>\u9ad8\u65af\u91d1\u5b57\u5854\uff1a\u5411\u4e0a\u91c7\u6837\u65b9\u6cd5\uff08\u653e\u5927\uff09<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/Pyramid_3.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">img=cv2.imread(&quot;AM.png&quot;)\ncv_show(img,&#039;img&#039;)\nprint (img.shape)<\/code><\/pre>\n<pre><code class=\"language-python\">up=cv2.pyrUp(img)\ncv_show(up,&#039;up&#039;)\nprint (up.shape)<\/code><\/pre>\n<pre><code class=\"language-python\">down=cv2.pyrDown(img)\ncv_show(down,&#039;down&#039;)\nprint (down.shape)<\/code><\/pre>\n<pre><code class=\"language-python\">up2=cv2.pyrUp(up)\ncv_show(up2,&#039;up2&#039;)\nprint (up2.shape)<\/code><\/pre>\n<pre><code class=\"language-python\">up=cv2.pyrUp(img)\nup_down=cv2.pyrDown(up)\ncv_show(up_down,&#039;up_down&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">cv_show(np.hstack((img,up_down)),&#039;up_down&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">up=cv2.pyrUp(img)\nup_down=cv2.pyrDown(up)\ncv_show(img-up_down,&#039;img-up_down&#039;)<\/code><\/pre>\n<h4>\u62c9\u666e\u62c9\u65af\u91d1\u5b57\u5854<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/Pyramid_4.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">down=cv2.pyrDown(img)\ndown_up=cv2.pyrUp(down)\nl_1=img-down_up\ncv_show(l_1,&#039;l_1&#039;)<\/code><\/pre>\n<h3>\u56fe\u50cf\u8f6e\u5ed3<\/h3>\n<h4>cv2.findContours(img,mode,method)<\/h4>\n<p>mode:\u8f6e\u5ed3\u68c0\u7d22\u6a21\u5f0f<\/p>\n<ul>\n<li>RETR_EXTERNAL \uff1a\u53ea\u68c0\u7d22\u6700\u5916\u9762\u7684\u8f6e\u5ed3\uff1b<\/li>\n<li>RETR_LIST\uff1a\u68c0\u7d22\u6240\u6709\u7684\u8f6e\u5ed3\uff0c\u5e76\u5c06\u5176\u4fdd\u5b58\u5230\u4e00\u6761\u94fe\u8868\u5f53\u4e2d\uff1b<\/li>\n<li>RETR_CCOMP\uff1a\u68c0\u7d22\u6240\u6709\u7684\u8f6e\u5ed3\uff0c\u5e76\u5c06\u4ed6\u4eec\u7ec4\u7ec7\u4e3a\u4e24\u5c42\uff1a\u9876\u5c42\u662f\u5404\u90e8\u5206\u7684\u5916\u90e8\u8fb9\u754c\uff0c\u7b2c\u4e8c\u5c42\u662f\u7a7a\u6d1e\u7684\u8fb9\u754c;<\/li>\n<li>RETR_TREE\uff1a\u68c0\u7d22\u6240\u6709\u7684\u8f6e\u5ed3\uff0c\u5e76\u91cd\u6784\u5d4c\u5957\u8f6e\u5ed3\u7684\u6574\u4e2a\u5c42\u6b21;<\/li>\n<\/ul>\n<p>method:\u8f6e\u5ed3\u903c\u8fd1\u65b9\u6cd5<\/p>\n<ul>\n<li>CHAIN_APPROX_NONE\uff1a\u4ee5Freeman\u94fe\u7801\u7684\u65b9\u5f0f\u8f93\u51fa\u8f6e\u5ed3\uff0c\u6240\u6709\u5176\u4ed6\u65b9\u6cd5\u8f93\u51fa\u591a\u8fb9\u5f62\uff08\u9876\u70b9\u7684\u5e8f\u5217\uff09\u3002<\/li>\n<li>CHAIN_APPROX_SIMPLE:\u538b\u7f29\u6c34\u5e73\u7684\u3001\u5782\u76f4\u7684\u548c\u659c\u7684\u90e8\u5206\uff0c\u4e5f\u5c31\u662f\uff0c\u51fd\u6570\u53ea\u4fdd\u7559\u4ed6\u4eec\u7684\u7ec8\u70b9\u90e8\u5206\u3002<\/li>\n<\/ul>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/chain.png\" alt=\"title\" \/><\/p>\n<p>\u4e3a\u4e86\u66f4\u9ad8\u7684\u51c6\u786e\u7387\uff0c\u4f7f\u7528\u4e8c\u503c\u56fe\u50cf\u3002<\/p>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;contours.png&#039;)\ngray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\nret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)\ncv_show(thresh,&#039;thresh&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">binary, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)<\/code><\/pre>\n<p>\u7ed8\u5236\u8f6e\u5ed3<\/p>\n<pre><code class=\"language-python\">cv_show(img,&#039;img&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">#\u4f20\u5165\u7ed8\u5236\u56fe\u50cf\uff0c\u8f6e\u5ed3\uff0c\u8f6e\u5ed3\u7d22\u5f15\uff0c\u989c\u8272\u6a21\u5f0f\uff0c\u7ebf\u6761\u539a\u5ea6\n# \u6ce8\u610f\u9700\u8981copy,\u8981\u4e0d\u539f\u56fe\u4f1a\u53d8\u3002\u3002\u3002\ndraw_img = img.copy()\nres = cv2.drawContours(draw_img, contours, -1, (0, 0, 255), 2)\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">draw_img = img.copy()\nres = cv2.drawContours(draw_img, contours, 0, (0, 0, 255), 2)\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<h4>\u8f6e\u5ed3\u7279\u5f81<\/h4>\n<pre><code class=\"language-python\">cnt = contours[0]<\/code><\/pre>\n<pre><code class=\"language-python\">#\u9762\u79ef\ncv2.contourArea(cnt)<\/code><\/pre>\n<pre><code class=\"language-python\">#\u5468\u957f\uff0cTrue\u8868\u793a\u95ed\u5408\u7684\ncv2.arcLength(cnt,True)<\/code><\/pre>\n<h4>\u8f6e\u5ed3\u8fd1\u4f3c<\/h4>\n<p><img src=\"https:\/\/lemon-guess.oss-cn-hangzhou.aliyuncs.com\/img\/contours3.png\" alt=\"title\" \/><\/p>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;contours2.png&#039;)\n\ngray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\nret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)\nbinary, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)\ncnt = contours[0]\n\ndraw_img = img.copy()\nres = cv2.drawContours(draw_img, [cnt], -1, (0, 0, 255), 2)\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">epsilon = 0.15*cv2.arcLength(cnt,True) \napprox = cv2.approxPolyDP(cnt,epsilon,True)\n\ndraw_img = img.copy()\nres = cv2.drawContours(draw_img, [approx], -1, (0, 0, 255), 2)\ncv_show(res,&#039;res&#039;)<\/code><\/pre>\n<p>\u8fb9\u754c\u77e9\u5f62<\/p>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;contours.png&#039;)\n\ngray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\nret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)\nbinary, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)\ncnt = contours[0]\n\nx,y,w,h = cv2.boundingRect(cnt)\nimg = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)\ncv_show(img,&#039;img&#039;)<\/code><\/pre>\n<pre><code class=\"language-python\">area = cv2.contourArea(cnt)\nx, y, w, h = cv2.boundingRect(cnt)\nrect_area = w * h\nextent = float(area) \/ rect_area\nprint (&#039;\u8f6e\u5ed3\u9762\u79ef\u4e0e\u8fb9\u754c\u77e9\u5f62\u6bd4&#039;,extent)<\/code><\/pre>\n<p>\u5916\u63a5\u5706<\/p>\n<pre><code class=\"language-python\">(x,y),radius = cv2.minEnclosingCircle(cnt) \ncenter = (int(x),int(y)) \nradius = int(radius) \nimg = cv2.circle(img,center,radius,(0,255,0),2)\ncv_show(img,&#039;img&#039;)<\/code><\/pre>\n<h3>\u5085\u91cc\u53f6\u53d8\u6362<\/h3>\n<p>\u6211\u4eec\u751f\u6d3b\u5728\u65f6\u95f4\u7684\u4e16\u754c\u4e2d\uff0c\u65e9\u4e0a7:00\u8d77\u6765\u5403\u65e9\u996d\uff0c8:00\u53bb\u6324\u5730\u94c1\uff0c9:00\u5f00\u59cb\u4e0a\u73ed\u3002\u3002\u3002\u4ee5\u65f6\u95f4\u4e3a\u53c2\u7167\u5c31\u662f\u65f6\u57df\u5206\u6790\u3002<\/p>\n<p>\u4f46\u662f\u5728\u9891\u57df\u4e2d\u4e00\u5207\u90fd\u662f\u9759\u6b62\u7684\uff01<\/p>\n<p><a href=\"https:\/\/zhuanlan.zhihu.com\/p\/19763358\">https:\/\/zhuanlan.zhihu.com\/p\/19763358<\/a><\/p>\n<h3>\u5085\u91cc\u53f6\u53d8\u6362\u7684\u4f5c\u7528<\/h3>\n<ul>\n<li>\n<p>\u9ad8\u9891\uff1a\u53d8\u5316\u5267\u70c8\u7684\u7070\u5ea6\u5206\u91cf\uff0c\u4f8b\u5982\u8fb9\u754c<\/p>\n<\/li>\n<li>\n<p>\u4f4e\u9891\uff1a\u53d8\u5316\u7f13\u6162\u7684\u7070\u5ea6\u5206\u91cf\uff0c\u4f8b\u5982\u4e00\u7247\u5927\u6d77<\/p>\n<\/li>\n<\/ul>\n<h3>\u6ee4\u6ce2<\/h3>\n<ul>\n<li>\n<p>\u4f4e\u901a\u6ee4\u6ce2\u5668\uff1a\u53ea\u4fdd\u7559\u4f4e\u9891\uff0c\u4f1a\u4f7f\u5f97\u56fe\u50cf\u6a21\u7cca<\/p>\n<\/li>\n<li>\n<p>\u9ad8\u901a\u6ee4\u6ce2\u5668\uff1a\u53ea\u4fdd\u7559\u9ad8\u9891\uff0c\u4f1a\u4f7f\u5f97\u56fe\u50cf\u7ec6\u8282\u589e\u5f3a<\/p>\n<\/li>\n<li>\n<p>opencv\u4e2d\u4e3b\u8981\u5c31\u662fcv2.dft()\u548ccv2.idft()\uff0c\u8f93\u5165\u56fe\u50cf\u9700\u8981\u5148\u8f6c\u6362\u6210np.float32 \u683c\u5f0f\u3002<\/p>\n<\/li>\n<li>\n<p>\u5f97\u5230\u7684\u7ed3\u679c\u4e2d\u9891\u7387\u4e3a0\u7684\u90e8\u5206\u4f1a\u5728\u5de6\u4e0a\u89d2\uff0c\u901a\u5e38\u8981\u8f6c\u6362\u5230\u4e2d\u5fc3\u4f4d\u7f6e\uff0c\u53ef\u4ee5\u901a\u8fc7shift\u53d8\u6362\u6765\u5b9e\u73b0\u3002<\/p>\n<\/li>\n<li>\n<p>cv2.dft()\u8fd4\u56de\u7684\u7ed3\u679c\u662f\u53cc\u901a\u9053\u7684\uff08\u5b9e\u90e8\uff0c\u865a\u90e8\uff09\uff0c\u901a\u5e38\u8fd8\u9700\u8981\u8f6c\u6362\u6210\u56fe\u50cf\u683c\u5f0f\u624d\u80fd\u5c55\u793a\uff080,255\uff09\u3002<\/p>\n<\/li>\n<\/ul>\n<pre><code class=\"language-python\">import numpy as np\nimport cv2\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread(&#039;lena.jpg&#039;,0)\n\nimg_float32 = np.float32(img)\n\ndft = cv2.dft(img_float32, flags = cv2.DFT_COMPLEX_OUTPUT)\ndft_shift = np.fft.fftshift(dft)\n# \u5f97\u5230\u7070\u5ea6\u56fe\u80fd\u8868\u793a\u7684\u5f62\u5f0f\nmagnitude_spectrum = 20*np.log(cv2.magnitude(dft_shift[:,:,0],dft_shift[:,:,1]))\n\nplt.subplot(121),plt.imshow(img, cmap = &#039;gray&#039;)\nplt.title(&#039;Input Image&#039;), plt.xticks([]), plt.yticks([])\nplt.subplot(122),plt.imshow(magnitude_spectrum, cmap = &#039;gray&#039;)\nplt.title(&#039;Magnitude Spectrum&#039;), plt.xticks([]), plt.yticks([])\nplt.show()<\/code><\/pre>\n<pre><code class=\"language-python\">import numpy as np\nimport cv2\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread(&#039;lena.jpg&#039;,0)\n\nimg_float32 = np.float32(img)\n\ndft = cv2.dft(img_float32, flags = cv2.DFT_COMPLEX_OUTPUT)\ndft_shift = np.fft.fftshift(dft)\n\nrows, cols = img.shape\ncrow, ccol = int(rows\/2) , int(cols\/2)     # \u4e2d\u5fc3\u4f4d\u7f6e\n\n# \u4f4e\u901a\u6ee4\u6ce2\nmask = np.zeros((rows, cols, 2), np.uint8)\nmask[crow-30:crow+30, ccol-30:ccol+30] = 1\n\n# IDFT\nfshift = dft_shift*mask\nf_ishift = np.fft.ifftshift(fshift)\nimg_back = cv2.idft(f_ishift)\nimg_back = cv2.magnitude(img_back[:,:,0],img_back[:,:,1])\n\nplt.subplot(121),plt.imshow(img, cmap = &#039;gray&#039;)\nplt.title(&#039;Input Image&#039;), plt.xticks([]), plt.yticks([])\nplt.subplot(122),plt.imshow(img_back, cmap = &#039;gray&#039;)\nplt.title(&#039;Result&#039;), plt.xticks([]), plt.yticks([])\n\nplt.show()                <\/code><\/pre>\n<pre><code class=\"language-python\">img = cv2.imread(&#039;lena.jpg&#039;,0)\n\nimg_float32 = np.float32(img)\n\ndft = cv2.dft(img_float32, flags = cv2.DFT_COMPLEX_OUTPUT)\ndft_shift = np.fft.fftshift(dft)\n\nrows, cols = img.shape\ncrow, ccol = int(rows\/2) , int(cols\/2)     # \u4e2d\u5fc3\u4f4d\u7f6e\n\n# \u9ad8\u901a\u6ee4\u6ce2\nmask = np.ones((rows, cols, 2), np.uint8)\nmask[crow-30:crow+30, ccol-30:ccol+30] = 0\n\n# IDFT\nfshift = dft_shift*mask\nf_ishift = np.fft.ifftshift(fshift)\nimg_back = cv2.idft(f_ishift)\nimg_back = cv2.magnitude(img_back[:,:,0],img_back[:,:,1])\n\nplt.subplot(121),plt.imshow(img, cmap = &#039;gray&#039;)\nplt.title(&#039;Input Image&#039;), plt.xticks([]), plt.yticks([])\nplt.subplot(122),plt.imshow(img_back, cmap = &#039;gray&#039;)\nplt.title(&#039;Result&#039;), plt.xticks([]), plt.yticks([])\n\nplt.show()    <\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>\u7070\u5ea6\u56fe import cv2 #opencv\u8bfb\u53d6\u7684\u683c\u5f0f\u662fBGR import numpy as np import matplotlib   \u2026 &#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ngg_post_thumbnail":0},"categories":[223],"tags":[],"_links":{"self":[{"href":"\/index.php?rest_route=\/wp\/v2\/posts\/9069"}],"collection":[{"href":"\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=9069"}],"version-history":[{"count":1,"href":"\/index.php?rest_route=\/wp\/v2\/posts\/9069\/revisions"}],"predecessor-version":[{"id":9070,"href":"\/index.php?rest_route=\/wp\/v2\/posts\/9069\/revisions\/9070"}],"wp:attachment":[{"href":"\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9069"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9069"},{"taxonomy":"post_tag","embeddable":true,"href":"\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9069"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}